Measuring Performance

After completing the questionnaires about their individual characteristics and momentary influences, the researcher verified correct positioning of the biometric sensor and calibrated the

recording system. For GSR, the sensors were always cleaned with an alcoholic-based gel and then placed on the pads of the index and middle fingers of the right hand and secured by Velcro. Then, the DataLab 2000 software provided an end-to-end calibration of the recording system. For fNIR, the Pucklink software’s Signal Quality Assessment tool was used to verify correct sensor placement by when it achieved an accurate heart rate and a heartbeat signal-to-noise ratio greater than 2.01. Actual heart rate was taken by the participant or researcher feeling for the pulse over a 30 second period or by using a pulse oximeter.

Next, the BioGauges system was calibrated according to the low and high values that each person was able to achieve at that moment. Detrending, a process for obtaining a moving average of values, was not incorporated into the BioGauges system because it was important to reduce bias for control. For GSR, participants were asked to relax for a low value and then think of something exciting and raised their temperature for a high value. Participants were asked to devise their own imagery since different things excite different people but to try to vary the images since people habituate over time and what was once exciting is no longer so. For fNIR, participants were asked to think of a non-sensical, droning sound created by repeating “la-la” slowly in their heads for a low value and then to think of counting rapidly but clearly enunciating each number in their heads for a high value. Participants then used this imagery to attempt control of each of the biometric interface technologies according to the protocol provided in Appendix D. Participants were tested with each of the biometric interface technologies in a randomly-ordered session and the trials within each session were also randomly ordered. An objective outcome measure of performance was taken after each trial using the BioGauges methodology and toolset. For this study, performance is the proportion of total trials in which a

1

All participants except DS38 achieved heartbeat signal-to-noise ratios greater than 2.0. After numerous adjustments of the sensor over a 5-minute period, the system was only able to achieve 1.83 with an accurate heart rate likely due to the overriding strength of the participant’s ventilator.

person is able to successfully move a cursor and acquire a bounded target within an allotted timeframe of twenty seconds.

BioGauges measure and characterize the capabilities of a user with a biometric interface technology (A.B. Randolph, McCampbell, Mason, & Moore, 2005; Adriane B. Randolph et al., 2007; Adriane B. Randolph, Melody Moore Jackson et al., 2005). They assess a user’s range, reliability, and granularity of control with a biometric interface technology based on very basic tasks. Specifically, gauges are very simple control interfaces that reflect changes in biometric phenomenon for the basic components of interaction. Gauges can be used to match a person to a particular biometric interface technology by producing an actual measure of performance

(Adriane B. Randolph et al., 2007).

Thus far, gauges have been designed to characterize controllability of discrete and

continuous transducers during periods when users intend to control their biometric input (i.e., Control State), such as when they wish to make a selection, and when they do not intend to control it (i.e., No Control State), such as when they are idly looking at the screen reviewing content. The protocols are summarized as follows. The protocols for continuous-output transducers are detailed in Appendix E.

For Discrete Output:

• Response to No Control

• Temporal accuracy to a predictable event • Response rate to an unpredictable event • Repetition rate

For Continuous Output: • Response to No Control

• Attain output levels (1-D) or point/region in 2-D or 3-D space

• Attain and hold output within a certain range of levels or region in space

This study incorporated a bounded attain task to test spatial control using an fNIR and a GSR-based biometric interface with continuous output. The bounded attain task is illustrated in Figure 13 and shows what the participant saw on his or her computer screen. Figure 14 shows what the researcher saw on her computer screen while monitoring the biometric phenomenon used to control the interface. Here, sample blood oxygenation readings appeared as the blue line at the top of the graph on the operator’s screen. The participant was asked to concentrate on the area with the black background and the screen to the left of the black background was used to set up and monitor the tasks. In this study, after the system provided a warning signal a cursor was presented as an orange square that always started in the middle of the screen. The participant attempted to activate the transducer to move the cursor along a one-dimensional track,

represented as the blue bar, to attain a target located to the right or left. The target was

represented by a yellow rectangle. A new trial started once the participant attained the target by placing the cursor completely within the target boundary lines or the system timed out. The participant had twenty seconds to attempt to attain the target before system timeout.

Figure 13. BioGauges interface for the Attain task

Figure 14. Pucklink interface for use with fNIR biometric interface technology with translating component for BioGauges interface

At the end of the session, each participant then completed an exit questionnaire provided in Appendix F.